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A Linear Prediction Based Estimation of Signal-to-Noise Ratio in AWGN Channel

Most signal-to-noise ratio (SNR) estimation techniques in digital communication channels derive the SNR estimates solely from samples of the received signal after the matched filter. They are based on symbol SNR and assume perfect synchronization and intersymbol interference (ISI)-free symbols....

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Main Author: Nidal S., Kamel
Format: Article
Published: ELECTRONICS TELECOMMUNICATIONS RESEARCH INST, 161 KAJONG-DONG, YUSONG-GU, TAEJON 305-350, SOUTH KOREA 2007
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://eprints.utp.edu.my/4486/1/29-05-05%5B1%5D.pdf
http://etrij.etri.re.kr/
http://eprints.utp.edu.my/4486/
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spelling my.utp.eprints.44862017-01-19T08:26:53Z A Linear Prediction Based Estimation of Signal-to-Noise Ratio in AWGN Channel Nidal S., Kamel TK Electrical engineering. Electronics Nuclear engineering Most signal-to-noise ratio (SNR) estimation techniques in digital communication channels derive the SNR estimates solely from samples of the received signal after the matched filter. They are based on symbol SNR and assume perfect synchronization and intersymbol interference (ISI)-free symbols. In severe channel distortion where ISI is significant, the performance of these estimators badly deteriorates. We propose an SNR estimator which can operate on data samples collected at the front-end of a receiver or at the input to the decision device. This will relax the restrictions over channel distortions and help extend the application of SNR estimators beyond system monitoring. The proposed estimator uses the characteristics of the second order moments of the additive white Gaussian noise digital communication channel and a linear predictor based on the modified-covariance algorithm in estimating the SNR value. The performance of the proposed technique is investigated and compared with other in-service SNR estimators in digital communication channels. The simulated performance is also compared to the Cramér- Rao bound as derived at the input of the decision circuit. ELECTRONICS TELECOMMUNICATIONS RESEARCH INST, 161 KAJONG-DONG, YUSONG-GU, TAEJON 305-350, SOUTH KOREA 2007-10 Article PeerReviewed application/pdf http://eprints.utp.edu.my/4486/1/29-05-05%5B1%5D.pdf http://etrij.etri.re.kr/ Nidal S., Kamel (2007) A Linear Prediction Based Estimation of Signal-to-Noise Ratio in AWGN Channel. ETRI JOURNAL, 29 (5). ISSN 1225-6463 http://eprints.utp.edu.my/4486/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Nidal S., Kamel
A Linear Prediction Based Estimation of Signal-to-Noise Ratio in AWGN Channel
description Most signal-to-noise ratio (SNR) estimation techniques in digital communication channels derive the SNR estimates solely from samples of the received signal after the matched filter. They are based on symbol SNR and assume perfect synchronization and intersymbol interference (ISI)-free symbols. In severe channel distortion where ISI is significant, the performance of these estimators badly deteriorates. We propose an SNR estimator which can operate on data samples collected at the front-end of a receiver or at the input to the decision device. This will relax the restrictions over channel distortions and help extend the application of SNR estimators beyond system monitoring. The proposed estimator uses the characteristics of the second order moments of the additive white Gaussian noise digital communication channel and a linear predictor based on the modified-covariance algorithm in estimating the SNR value. The performance of the proposed technique is investigated and compared with other in-service SNR estimators in digital communication channels. The simulated performance is also compared to the Cramér- Rao bound as derived at the input of the decision circuit.
format Article
author Nidal S., Kamel
author_facet Nidal S., Kamel
author_sort Nidal S., Kamel
title A Linear Prediction Based Estimation of Signal-to-Noise Ratio in AWGN Channel
title_short A Linear Prediction Based Estimation of Signal-to-Noise Ratio in AWGN Channel
title_full A Linear Prediction Based Estimation of Signal-to-Noise Ratio in AWGN Channel
title_fullStr A Linear Prediction Based Estimation of Signal-to-Noise Ratio in AWGN Channel
title_full_unstemmed A Linear Prediction Based Estimation of Signal-to-Noise Ratio in AWGN Channel
title_sort linear prediction based estimation of signal-to-noise ratio in awgn channel
publisher ELECTRONICS TELECOMMUNICATIONS RESEARCH INST, 161 KAJONG-DONG, YUSONG-GU, TAEJON 305-350, SOUTH KOREA
publishDate 2007
url http://eprints.utp.edu.my/4486/1/29-05-05%5B1%5D.pdf
http://etrij.etri.re.kr/
http://eprints.utp.edu.my/4486/
_version_ 1738655344892051456
score 13.211869

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